N2O valence (orbs 6 - 9) ePS results processing¶
20/03/24
Added basic MF-PAD results (linear polarization, $(x,y,z)$ alignments).
22/02/24 PH
1st processing for N2O results.
For methods: https://epsproc.readthedocs.io/en/dev/demos/ePSproc_class_demo_161020.html
Setup¶
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# Quick hack to override default HTML template
# NOT required in some JLab versions.
# https://stackoverflow.com/a/63777508
# https://stackoverflow.com/questions/21971449/how-do-i-increase-the-cell-width-of-the-jupyter-ipython-notebook-in-my-browser
from IPython.core.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
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import sys
import os
from pathlib import Path
import numpy as np
# import epsproc as ep
import xarray as xr
import matplotlib.pyplot as plt
from datetime import datetime as dt
timeString = dt.now()
import epsproc as ep
# Plotters
from epsproc.plot import hvPlotters
# Multijob class dev code
from epsproc.classes.multiJob import ePSmultiJob
hvPlotters.setPlotters(width = 700, snsStyle='whitegrid')
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# For class, above settings don't take, not sure why, something to do with namespaces/calling sequence?
# Overriding snsStyle does work however... although NOT CONSISTENTLY????
# AH, looks like ordering matters - set_style LAST (.set seems to override)
import seaborn as sns
sns.set(rc={'figure.figsize':(10,6)}) # Set figure size in inches
sns.set_context("paper")
sns.set_style("whitegrid") # Set plot style
sns.set_palette("Paired") # Set colour mapping
# Try direct fig type setting for PDF output figs
from IPython.display import set_matplotlib_formats
# set_matplotlib_formats('png', 'pdf')
set_matplotlib_formats('svg', 'pdf')
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# xr.set_options(display_style='html')
Load data¶
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import warnings
# warnings.filterwarnings('once') # Skip repeated numpy deprecation warnings in current build (xr15 env)
warnings.filterwarnings('ignore') # Skip repeated numpy deprecation warnings in current build (xr15 env)
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# # Scan for subdirs, based on existing routine in getFiles()
# fileBase = Path('/home/paul/ePS/OCS/OCS_survey') # Data dir on Stimpy
fileBase = Path('/home/paul/fock-mount/globalhome/eps/N2O/N2O_valence') # Data dir on Jake
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# TODO: fix orb label here, currently relies on (different) fixed format
data = ePSmultiJob(fileBase, verbose = 0)
data.scanFiles()
data.jobsSummary()
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# # Fix labels for plots
# for key in data.data.keys():
# data.data[key]['jobNotes']['orbLabel'] = key
System properties¶
Note orbital numbering in table below:
Orbis Gamess file output orbital numbering, ordered by energy but not grouped by degeneracy.OrbGrpis grouped numbering by degeneracy, also used by ePolyScat, and will be used for labels etc. below.
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data.molSummary()
Plot cross-sections and betas¶
These are from ePolyScat's getCro function, and are LF (unaligned ensemble) results. This provides a good, if general, overview.
Overview (all symmetries, length gauge) vs. Eke¶
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# NEED TO SET AGAIN AFTER CLASS IMPORT!
import warnings
# warnings.filterwarnings('once') # Skip repeated numpy deprecation warnings in current build (xr15 env)
warnings.filterwarnings('ignore') # Skip repeated numpy deprecation warnings in current build (xr15 env)
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# Comparative plot over datasets (all symmetries only)
Etype = 'Eke' # Set for Eke or Ehv energy scale
pGauge = 'L'
# Erange=[0, 100] # Plot range (full range if not passed to function below)
# data.plotGetCroComp(pType='SIGMA', Etype = Etype, Erange = Erange, backend = 'hv')
data.plotGetCroComp(pType='SIGMA', pGauge = pGauge, Etype = Etype)
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# Comparative plot over datasets (all symmetries only)
data.plotGetCroComp(pType='BETA', Etype=Etype)
Overview (all symmetries, length gauge) vs. Ehv¶
Same results as above, Ehv scale.
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# Comparative plot over datasets (all symmetries only)
Etype = 'Ehv' # Set for Eke or Ehv energy scale
pGauge = 'L'
# Erange=[0, 100] # Plot range (full range if not passed to function below)
# data.plotGetCroComp(pType='SIGMA', Etype = Etype, Erange = Erange, backend = 'hv')
data.plotGetCroComp(pType='SIGMA', pGauge = pGauge, Etype = Etype)
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# Comparative plot over datasets (all symmetries only)
data.plotGetCroComp(pType='BETA', Etype=Etype)
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# TODO
# data.plotGetCroComp(pType='BETA', Etype=Etype, backend='hv')
Checks¶
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# Betas vs. Gauge
data.plotGetCro(pType='BETA', Etype=Etype)
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Compute MF observables¶
MF-$\beta_{LM}$¶
Compute MF results for $(x,y,z)$ polarization geometry (linear polarization).
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data.MFBLM()
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data.BLMplot(dataType='MFBLM', thres = 1e-2, backend='hv') # Passing a threshold value here will remove any spurious BLM parameters.
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MF-PADs $(\theta,E)$ for $\phi$-summed case)¶
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# Compute MFPADs from BLMs and sum over phi.
data.padPlot(dataType='MFBLM',
pStyle='grid', reducePhi='sum') #, backend='hv')
Versions¶
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# print(data.jobInfo['ePolyScat'][0])
# print('Run: ' + jobInfo['Starting'][0].split('at')[1])
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import scooby
scooby.Report(additional=['epsproc', 'xarray', 'jupyter'])
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# Check current Git commit for local ePSproc version
!git -C {Path(ep.__file__).parent} branch
!git -C {Path(ep.__file__).parent} log --format="%H" -n 1
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# Check current remote commits
!git ls-remote --heads https://github.com/phockett/ePSproc
Env¶
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!hostname
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!conda env list
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